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Add YOLOv5-cls Model (#335)
* add yolov5cls * fixed bugs * fixed bugs * fixed preprocess bug * add yolov5cls readme * deal with comments * Add YOLOv5Cls Note * add yolov5cls test Co-authored-by: Jason <jiangjiajun@baidu.com>
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examples/vision/classification/yolov5cls/python/README.md
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# YOLOv5Cls Python部署示例
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在部署前,需确认以下两个步骤
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- 1. 软硬件环境满足要求,参考[FastDeploy环境要求](../../../../../docs/environment.md)
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- 2. FastDeploy Python whl包安装,参考[FastDeploy Python安装](../../../../../docs/quick_start)
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本目录下提供`infer.py`快速完成YOLOv5Cls在CPU/GPU,以及GPU上通过TensorRT加速部署的示例。执行如下脚本即可完成
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```bash
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#下载部署示例代码
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git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd examples/vision/classification/yolov5cls/python/
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#下载yolov5cls模型文件和测试图片
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wget https://bj.bcebos.com/paddlehub/fastdeploy/yolov5n-cls.onnx
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wget https://gitee.com/paddlepaddle/PaddleClas/raw/release/2.4/deploy/images/ImageNet/ILSVRC2012_val_00000010.jpeg
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# CPU推理
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python infer.py --model yolov5n-cls.onnx --image ILSVRC2012_val_00000010.jpeg --device cpu --topk 1
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# GPU推理
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python infer.py --model yolov5n-cls.onnx --image ILSVRC2012_val_00000010.jpeg --device gpu --topk 1
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# GPU上使用TensorRT推理
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python infer.py --model yolov5n-cls.onnx --image ILSVRC2012_val_00000010.jpeg --device gpu --use_trt True
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```
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运行完成后返回结果如下所示
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```bash
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ClassifyResult(
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label_ids: 265,
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scores: 0.196327,
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)
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```
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## YOLOv5Cls Python接口
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```python
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fastdeploy.vision.classification.YOLOv5Cls(model_file, params_file=None, runtime_option=None, model_format=ModelFormat.ONNX)
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```
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YOLOv5Cls模型加载和初始化,其中model_file为导出的ONNX模型格式
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**参数**
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> * **model_file**(str): 模型文件路径
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> * **params_file**(str): 参数文件路径,当模型格式为ONNX格式时,此参数无需设定
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> * **runtime_option**(RuntimeOption): 后端推理配置,默认为None,即采用默认配置
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> * **model_format**(ModelFormat): 模型格式,默认为ONNX
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### predict函数
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> ```python
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> YOLOv5Cls.predict(image_data, topk=1)
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> ```
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>
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> 模型预测结口,输入图像直接输出分类topk结果。
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>
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> **参数**
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>
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> > * **input_image**(np.ndarray): 输入数据,注意需为HWC,BGR格式
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> > * **topk**(int):返回预测概率最高的topk个分类结果,默认为1
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> **返回**
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>
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> > 返回`fastdeploy.vision.ClassifyResult`结构体,结构体说明参考文档[视觉模型预测结果](../../../../../docs/api/vision_results/)
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## 其它文档
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- [YOLOv5Cls 模型介绍](..)
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- [YOLOv5Cls C++部署](../cpp)
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- [模型预测结果说明](../../../../../docs/api/vision_results/)
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- [如何切换模型推理后端引擎](../../../../../docs/runtime/how_to_change_backend.md)
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